Reporte de Datos Tutorial

Dataset statistics

Number of variables	20
Number of observations	17858
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	1.7 MiB
Average record size in memory	97.2 B

Variable types

Numeric	16
Categorical	4

Warnings

`prom_bill_amt` is highly correlated with `pay_amt1` and 5 other fields	High correlation
`pay_amt1` is highly correlated with `prom_bill_amt`	High correlation
`pay_amt2` is highly correlated with `prom_bill_amt`	High correlation
`pay_amt3` is highly correlated with `prom_bill_amt` and 2 other fields	High correlation
`pay_amt4` is highly correlated with `prom_bill_amt` and 2 other fields	High correlation
`pay_amt5` is highly correlated with `prom_bill_amt` and 3 other fields	High correlation
`pay_amt6` is highly correlated with `prom_bill_amt` and 3 other fields	High correlation
`prom_bill_amt` is highly correlated with `pay_amt1` and 5 other fields	High correlation
`pay_amt1` is highly correlated with `prom_bill_amt` and 1 other fields	High correlation
`pay_amt2` is highly correlated with `prom_bill_amt` and 2 other fields	High correlation
`pay_amt3` is highly correlated with `prom_bill_amt` and 4 other fields	High correlation
`pay_amt4` is highly correlated with `prom_bill_amt` and 4 other fields	High correlation
`pay_amt5` is highly correlated with `prom_bill_amt` and 4 other fields	High correlation
`pay_amt6` is highly correlated with `prom_bill_amt` and 3 other fields	High correlation
`df_index` is highly correlated with `default.payment.next.month`	High correlation
`limit_bal` is highly correlated with `default.payment.next.month`	High correlation
`age` is highly correlated with `default.payment.next.month`	High correlation
`prom_bill_amt` is highly correlated with `default.payment.next.month`	High correlation
`pay_amt1` is highly correlated with `default.payment.next.month`	High correlation
`pay_amt2` is highly correlated with `default.payment.next.month`	High correlation
`pay_amt3` is highly correlated with `default.payment.next.month`	High correlation
`pay_amt4` is highly correlated with `default.payment.next.month`	High correlation
`pay_amt5` is highly correlated with `default.payment.next.month`	High correlation
`pay_amt6` is highly correlated with `default.payment.next.month`	High correlation
`default.payment.next.month` is highly correlated with `df_index` and 9 other fields	High correlation
`pay_amt1` is highly correlated with `pay_amt2` and 7 other fields	High correlation
`pay_4` is highly correlated with `pay_2` and 5 other fields	High correlation
`marriage` is highly correlated with `age`	High correlation
`pay_amt2` is highly correlated with `pay_amt1` and 6 other fields	High correlation
`default.payment.next.month` is highly correlated with `pay_1`	High correlation
`pay_amt4` is highly correlated with `pay_amt1` and 5 other fields	High correlation
`pay_amt3` is highly correlated with `pay_amt1` and 5 other fields	High correlation
`pay_2` is highly correlated with `pay_amt1` and 7 other fields	High correlation
`pay_amt6` is highly correlated with `pay_amt1` and 5 other fields	High correlation
`pay_5` is highly correlated with `pay_4` and 5 other fields	High correlation
`pay_1` is highly correlated with `pay_amt1` and 6 other fields	High correlation
`pay_6` is highly correlated with `pay_4` and 5 other fields	High correlation
`age` is highly correlated with `marriage`	High correlation
`prom_bill_amt` is highly correlated with `pay_amt1` and 10 other fields	High correlation
`pay_3` is highly correlated with `pay_4` and 5 other fields	High correlation
`pay_amt5` is highly correlated with `pay_amt1` and 5 other fields	High correlation
`df_index` has unique values	Unique
`pay_1` has 8707 (48.8%) zeros	Zeros
`pay_2` has 9437 (52.8%) zeros	Zeros
`pay_3` has 9403 (52.7%) zeros	Zeros
`pay_4` has 9663 (54.1%) zeros	Zeros
`pay_5` has 9870 (55.3%) zeros	Zeros
`pay_6` has 9481 (53.1%) zeros	Zeros
`prom_bill_amt` has 834 (4.7%) zeros	Zeros
`pay_amt1` has 3982 (22.3%) zeros	Zeros
`pay_amt2` has 4180 (23.4%) zeros	Zeros
`pay_amt3` has 4575 (25.6%) zeros	Zeros
`pay_amt4` has 4923 (27.6%) zeros	Zeros
`pay_amt5` has 5176 (29.0%) zeros	Zeros
`pay_amt6` has 5575 (31.2%) zeros	Zeros

Reproduction

Analysis started	2021-09-30 00:57:13.007260
Analysis finished	2021-09-30 00:57:59.290023
Duration	46.28 seconds
Software version	pandas-profiling v3.0.0
Download configuration	config.json

df_index
Real number (ℝ_≥0)

HIGH CORRELATION
UNIQUE

Distinct	17858
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	14848.82305

Minimum	0
Maximum	29999
Zeros	1
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	139.6 KiB

Quantile statistics

Minimum	0
5-th percentile	1466.85
Q1	7412.25
median	14872.5
Q3	22105.75
95-th percentile	28481.15
Maximum	29999
Range	29999
Interquartile range (IQR)	14693.5

Descriptive statistics

Standard deviation	8614.799685
Coefficient of variation (CV)	0.5801671726
Kurtosis	-1.1759603
Mean	14848.82305
Median Absolute Deviation (MAD)	7354.5
Skewness	0.02364426411
Sum	265170282
Variance	74214773.61
Monotonicity	Strictly increasing

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	1	< 0.1%
19601	1	< 0.1%
19612	1	< 0.1%
19607	1	< 0.1%
19606	1	< 0.1%
19604	1	< 0.1%
19603	1	< 0.1%
19602	1	< 0.1%
19599	1	< 0.1%
19573	1	< 0.1%
Other values (17848)	17848	99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	1	< 0.1%
2	1	< 0.1%
3	1	< 0.1%
5	1	< 0.1%
7	1	< 0.1%
8	1	< 0.1%
10	1	< 0.1%
13	1	< 0.1%
14	1	< 0.1%

Value	Count	Frequency (%)
29999	1	< 0.1%
29992	1	< 0.1%
29991	1	< 0.1%
29990	1	< 0.1%
29989	1	< 0.1%
29986	1	< 0.1%
29985	1	< 0.1%
29984	1	< 0.1%
29982	1	< 0.1%
29981	1	< 0.1%

limit_bal
Real number (ℝ_≥0)

HIGH CORRELATION

Distinct	53
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	127132.4896

Minimum	10000
Maximum	520000
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	139.6 KiB

Quantile statistics

Minimum	10000
5-th percentile	20000
Q1	50000
median	90000
Q3	180000
95-th percentile	360000
Maximum	520000
Range	510000
Interquartile range (IQR)	130000

Descriptive statistics

Standard deviation	106425.0419
Coefficient of variation (CV)	0.8371191522
Kurtosis	1.141738625
Mean	127132.4896
Median Absolute Deviation (MAD)	60000
Skewness	1.247992433
Sum	2270332000
Variance	1.132628955 × 10¹⁰
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
50000	2686	15.0%
20000	1665	9.3%
30000	1356	7.6%
80000	1118	6.3%
100000	739	4.1%
200000	699	3.9%
60000	610	3.4%
70000	571	3.2%
150000	562	3.1%
180000	535	3.0%
Other values (43)	7317	41.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
10000	442	2.5%
16000	2	< 0.1%
20000	1665	9.3%
30000	1356	7.6%
40000	189	1.1%
50000	2686	15.0%
60000	610	3.4%
70000	571	3.2%
80000	1118	6.3%
90000	449	2.5%

Value	Count	Frequency (%)
520000	3	< 0.1%
510000	4	< 0.1%
500000	153	0.9%
490000	9	0.1%
480000	14	0.1%
470000	19	0.1%
460000	17	0.1%
450000	63	0.4%
440000	15	0.1%
430000	21	0.1%

sex
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	17.7 KiB

2	10721
1	7137

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	17858
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2
2nd row	2
3rd row	2
4th row	2
5th row	1

Common Values

Value	Count	Frequency (%)
2	10721	60.0%
1	7137	40.0%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2	10721	60.0%
1	7137	40.0%

Most occurring characters

Value	Count	Frequency (%)
2	10721	60.0%
1	7137	40.0%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	17858	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
2	10721	60.0%
1	7137	40.0%

Most occurring scripts

Value	Count	Frequency (%)
Common	17858	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
2	10721	60.0%
1	7137	40.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	17858	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
2	10721	60.0%
1	7137	40.0%

education
Categorical

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	17.8 KiB

2	8842
1	5530
3	3245
5	179
4	62

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	17858
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2
2nd row	2
3rd row	2
4th row	2
5th row	1

Common Values

Value	Count	Frequency (%)
2	8842	49.5%
1	5530	31.0%
3	3245	18.2%
5	179	1.0%
4	62	0.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2	8842	49.5%
1	5530	31.0%
3	3245	18.2%
5	179	1.0%
4	62	0.3%

Most occurring characters

Value	Count	Frequency (%)
2	8842	49.5%
1	5530	31.0%
3	3245	18.2%
5	179	1.0%
4	62	0.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	17858	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
2	8842	49.5%
1	5530	31.0%
3	3245	18.2%
5	179	1.0%
4	62	0.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	17858	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
2	8842	49.5%
1	5530	31.0%
3	3245	18.2%
5	179	1.0%
4	62	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	17858	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
2	8842	49.5%
1	5530	31.0%
3	3245	18.2%
5	179	1.0%
4	62	0.3%

marriage
Categorical

HIGH CORRELATION

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	17.7 KiB

2	9586
1	8014
3	258

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	17858
Distinct characters	3
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	2
3rd row	2
4th row	1
5th row	2

Common Values

Value	Count	Frequency (%)
2	9586	53.7%
1	8014	44.9%
3	258	1.4%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
2	9586	53.7%
1	8014	44.9%
3	258	1.4%

Most occurring characters

Value	Count	Frequency (%)
2	9586	53.7%
1	8014	44.9%
3	258	1.4%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	17858	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
2	9586	53.7%
1	8014	44.9%
3	258	1.4%

Most occurring scripts

Value	Count	Frequency (%)
Common	17858	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
2	9586	53.7%
1	8014	44.9%
3	258	1.4%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	17858	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
2	9586	53.7%
1	8014	44.9%
3	258	1.4%

age
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION

Distinct	40
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	35.02391085

Minimum	21
Maximum	60
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	139.6 KiB

Quantile statistics

Minimum	21
5-th percentile	23
Q1	27
median	33
Q3	41
95-th percentile	53
Maximum	60
Range	39
Interquartile range (IQR)	14

Descriptive statistics

Standard deviation	9.195665975
Coefficient of variation (CV)	0.2625539453
Kurtosis	-0.5065206304
Mean	35.02391085
Median Absolute Deviation (MAD)	7
Skewness	0.6024361118
Sum	625457
Variance	84.56027273
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=40)

Value	Count	Frequency (%)
29	920	5.2%
27	910	5.1%
25	821	4.6%
24	818	4.6%
26	808	4.5%
28	798	4.5%
30	759	4.3%
23	691	3.9%
31	680	3.8%
34	641	3.6%
Other values (30)	10012	56.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
21	58	0.3%
22	460	2.6%
23	691	3.9%
24	818	4.6%
25	821	4.6%
26	808	4.5%
27	910	5.1%
28	798	4.5%
29	920	5.2%
30	759	4.3%

Value	Count	Frequency (%)
60	52	0.3%
59	63	0.4%
58	84	0.5%
57	79	0.4%
56	131	0.7%
55	137	0.8%
54	165	0.9%
53	204	1.1%
52	203	1.1%
51	216	1.2%

pay_1
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct	11
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.1180983313

Minimum	-2
Maximum	8
Zeros	8707
Zeros (%)	48.8%
Negative	4213
Negative (%)	23.6%
Memory size	139.6 KiB

Quantile statistics

Minimum	-2
5-th percentile	-2
Q1	0
median	0
Q3	1
95-th percentile	2
Maximum	8
Range	10
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.156992145
Coefficient of variation (CV)	9.796854304
Kurtosis	2.536265681
Mean	0.1180983313
Median Absolute Deviation (MAD)	1
Skewness	0.6813061545
Sum	2109
Variance	1.338630824
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
0	8707	48.8%
-1	2740	15.3%
1	2662	14.9%
2	1905	10.7%
-2	1473	8.2%
3	268	1.5%
4	57	0.3%
5	18	0.1%
8	14	0.1%
6	9	0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-2	1473	8.2%
-1	2740	15.3%
0	8707	48.8%
1	2662	14.9%
2	1905	10.7%
3	268	1.5%
4	57	0.3%
5	18	0.1%
6	9	0.1%
7	5	< 0.1%

Value	Count	Frequency (%)
8	14	0.1%
7	5	< 0.1%
6	9	0.1%
5	18	0.1%
4	57	0.3%
3	268	1.5%
2	1905	10.7%
1	2662	14.9%
0	8707	48.8%
-1	2740	15.3%

pay_2
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct	11
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-0.01926307537

Minimum	-2
Maximum	8
Zeros	9437
Zeros (%)	52.8%
Negative	5139
Negative (%)	28.8%
Memory size	139.6 KiB

Quantile statistics

Minimum	-2
5-th percentile	-2
Q1	-1
median	0
Q3	0
95-th percentile	2
Maximum	8
Range	10
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.272506923
Coefficient of variation (CV)	-66.05938558
Kurtosis	1.098353621
Mean	-0.01926307537
Median Absolute Deviation (MAD)	0
Skewness	0.680905606
Sum	-344
Variance	1.61927387
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=11)

Value	Count	Frequency (%)
0	9437	52.8%
2	2893	16.2%
-1	2791	15.6%
-2	2348	13.1%
3	255	1.4%
4	82	0.5%
5	20	0.1%
7	15	0.1%
1	9	0.1%
6	7	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-2	2348	13.1%
-1	2791	15.6%
0	9437	52.8%
1	9	0.1%
2	2893	16.2%
3	255	1.4%
4	82	0.5%
5	20	0.1%
6	7	< 0.1%
7	15	0.1%

Value	Count	Frequency (%)
8	1	< 0.1%
7	15	0.1%
6	7	< 0.1%
5	20	0.1%
4	82	0.5%
3	255	1.4%
2	2893	16.2%
1	9	0.1%
0	9437	52.8%
-1	2791	15.6%

pay_3
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct	10
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-0.06837271811

Minimum	-2
Maximum	8
Zeros	9403
Zeros (%)	52.7%
Negative	5339
Negative (%)	29.9%
Memory size	139.6 KiB

Quantile statistics

Minimum	-2
5-th percentile	-2
Q1	-1
median	0
Q3	0
95-th percentile	2
Maximum	8
Range	10
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.288646667
Coefficient of variation (CV)	-18.84738098
Kurtosis	1.705159725
Mean	-0.06837271811
Median Absolute Deviation (MAD)	0
Skewness	0.761167977
Sum	-1221
Variance	1.660610232
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
0	9403	52.7%
2	2798	15.7%
-2	2688	15.1%
-1	2651	14.8%
3	198	1.1%
4	60	0.3%
7	26	0.1%
6	18	0.1%
5	14	0.1%
8	2	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-2	2688	15.1%
-1	2651	14.8%
0	9403	52.7%
2	2798	15.7%
3	198	1.1%
4	60	0.3%
5	14	0.1%
6	18	0.1%
7	26	0.1%
8	2	< 0.1%

Value	Count	Frequency (%)
8	2	< 0.1%
7	26	0.1%
6	18	0.1%
5	14	0.1%
4	60	0.3%
3	198	1.1%
2	2798	15.7%
0	9403	52.7%
-1	2651	14.8%
-2	2688	15.1%

pay_4
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct	10
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-0.1504087804

Minimum	-2
Maximum	8
Zeros	9663
Zeros (%)	54.1%
Negative	5578
Negative (%)	31.2%
Memory size	139.6 KiB

Quantile statistics

Minimum	-2
5-th percentile	-2
Q1	-1
median	0
Q3	0
95-th percentile	2
Maximum	8
Range	10
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.279630108
Coefficient of variation (CV)	-8.507682228
Kurtosis	3.097011255
Mean	-0.1504087804
Median Absolute Deviation (MAD)	0
Skewness	0.9839738753
Sum	-2686
Variance	1.637453213
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
0	9663	54.1%
-2	2980	16.7%
-1	2598	14.5%
2	2329	13.0%
3	145	0.8%
7	56	0.3%
4	54	0.3%
5	29	0.2%
6	3	< 0.1%
8	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-2	2980	16.7%
-1	2598	14.5%
0	9663	54.1%
2	2329	13.0%
3	145	0.8%
4	54	0.3%
5	29	0.2%
6	3	< 0.1%
7	56	0.3%
8	1	< 0.1%

Value	Count	Frequency (%)
8	1	< 0.1%
7	56	0.3%
6	3	< 0.1%
5	29	0.2%
4	54	0.3%
3	145	0.8%
2	2329	13.0%
0	9663	54.1%
-1	2598	14.5%
-2	2980	16.7%

pay_5
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct	10
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-0.220853399

Minimum	-2
Maximum	8
Zeros	9870
Zeros (%)	55.3%
Negative	5778
Negative (%)	32.4%
Memory size	139.6 KiB

Quantile statistics

Minimum	-2
5-th percentile	-2
Q1	-1
median	0
Q3	0
95-th percentile	2
Maximum	8
Range	10
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.247385218
Coefficient of variation (CV)	-5.648023638
Kurtosis	3.592689755
Mean	-0.220853399
Median Absolute Deviation (MAD)	0
Skewness	1.030325462
Sum	-3944
Variance	1.555969883
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
0	9870	55.3%
-2	3199	17.9%
-1	2579	14.4%
2	1924	10.8%
3	146	0.8%
4	69	0.4%
7	55	0.3%
5	12	0.1%
6	3	< 0.1%
8	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-2	3199	17.9%
-1	2579	14.4%
0	9870	55.3%
2	1924	10.8%
3	146	0.8%
4	69	0.4%
5	12	0.1%
6	3	< 0.1%
7	55	0.3%
8	1	< 0.1%

Value	Count	Frequency (%)
8	1	< 0.1%
7	55	0.3%
6	3	< 0.1%
5	12	0.1%
4	69	0.4%
3	146	0.8%
2	1924	10.8%
0	9870	55.3%
-1	2579	14.4%
-2	3199	17.9%

pay_6
Real number (ℝ)

HIGH CORRELATION
ZEROS

Distinct	10
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	-0.2645872998

Minimum	-2
Maximum	8
Zeros	9481
Zeros (%)	53.1%
Negative	6169
Negative (%)	34.5%
Memory size	139.6 KiB

Quantile statistics

Minimum	-2
5-th percentile	-2
Q1	-1
median	0
Q3	0
95-th percentile	2
Maximum	8
Range	10
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.258021805
Coefficient of variation (CV)	-4.754656802
Kurtosis	3.100133647
Mean	-0.2645872998
Median Absolute Deviation (MAD)	0
Skewness	0.9638072866
Sum	-4725
Variance	1.582618861
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=10)

Value	Count	Frequency (%)
0	9481	53.1%
-2	3518	19.7%
-1	2651	14.8%
2	1944	10.9%
3	157	0.9%
7	46	0.3%
4	39	0.2%
6	12	0.1%
5	9	0.1%
8	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-2	3518	19.7%
-1	2651	14.8%
0	9481	53.1%
2	1944	10.9%
3	157	0.9%
4	39	0.2%
5	9	0.1%
6	12	0.1%
7	46	0.3%
8	1	< 0.1%

Value	Count	Frequency (%)
8	1	< 0.1%
7	46	0.3%
6	12	0.1%
5	9	0.1%
4	39	0.2%
3	157	0.9%
2	1944	10.9%
0	9481	53.1%
-1	2651	14.8%
-2	3518	19.7%

prom_bill_amt
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	15803
Distinct (%)	88.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	26808.36984

Minimum	-43253.83333
Maximum	134098.5
Zeros	834
Zeros (%)	4.7%
Negative	162
Negative (%)	0.9%
Memory size	139.6 KiB

Quantile statistics

Minimum	-43253.83333
5-th percentile	0
Q1	1847.875
median	17242.91667
Q3	40623.29167
95-th percentile	93056.875
Maximum	134098.5
Range	177352.3333
Interquartile range (IQR)	38775.41667

Descriptive statistics

Standard deviation	30282.80622
Coefficient of variation (CV)	1.129602673
Kurtosis	1.30972247
Mean	26808.36984
Median Absolute Deviation (MAD)	16233.83333
Skewness	1.369884113
Sum	478743868.7
Variance	917048352.8
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	834	4.7%
390	54	0.3%
416.6666667	31	0.2%
2400	29	0.2%
325	25	0.1%
1050	21	0.1%
455	21	0.1%
326	20	0.1%
316	18	0.1%
260	18	0.1%
Other values (15793)	16787	94.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
-43253.83333	1	< 0.1%
-13255	1	< 0.1%
-6467.833333	1	< 0.1%
-5109.666667	1	< 0.1%
-4913.333333	1	< 0.1%
-4894	1	< 0.1%
-2997	1	< 0.1%
-2916.666667	1	< 0.1%
-2900	1	< 0.1%
-2851.5	1	< 0.1%

Value	Count	Frequency (%)
134098.5	1	< 0.1%
133989.5	1	< 0.1%
133779.3333	1	< 0.1%
133698.8333	1	< 0.1%
133576.5	1	< 0.1%
133223.5	1	< 0.1%
133218.5	1	< 0.1%
133048.1667	1	< 0.1%
132985.5	1	< 0.1%
132780.3333	1	< 0.1%

pay_amt1
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	3804
Distinct (%)	21.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1978.817617

Minimum	0
Maximum	9156
Zeros	3982
Zeros (%)	22.3%
Negative	0
Negative (%)	0.0%
Memory size	139.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	316
median	1700
Q3	3000
95-th percentile	5541.2
Maximum	9156
Range	9156
Interquartile range (IQR)	2684

Descriptive statistics

Standard deviation	1820.160726
Coefficient of variation (CV)	0.9198223781
Kurtosis	0.9693086281
Mean	1978.817617
Median Absolute Deviation (MAD)	1300
Skewness	1.060384336
Sum	35337725
Variance	3312985.068
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	3982	22.3%
2000	1135	6.4%
3000	661	3.7%
1500	445	2.5%
5000	393	2.2%
4000	286	1.6%
2500	251	1.4%
1000	245	1.4%
1300	164	0.9%
390	163	0.9%
Other values (3794)	10133	56.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	3982	22.3%
1	7	< 0.1%
2	8	< 0.1%
3	10	0.1%
4	9	0.1%
5	3	< 0.1%
6	8	< 0.1%
7	4	< 0.1%
8	2	< 0.1%
9	3	< 0.1%

Value	Count	Frequency (%)
9156	1	< 0.1%
9148	1	< 0.1%
9117	1	< 0.1%
9054	1	< 0.1%
9052	1	< 0.1%
9048	1	< 0.1%
9026	1	< 0.1%
9004	1	< 0.1%
9000	17	0.1%
8992	1	< 0.1%

pay_amt2
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	3592
Distinct (%)	20.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1818.778979

Minimum	0
Maximum	8090
Zeros	4180
Zeros (%)	23.4%
Negative	0
Negative (%)	0.0%
Memory size	139.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	199.25
median	1522
Q3	2750.75
95-th percentile	5016
Maximum	8090
Range	8090
Interquartile range (IQR)	2551.5

Descriptive statistics

Standard deviation	1677.681371
Coefficient of variation (CV)	0.9224217954
Kurtosis	0.681896554
Mean	1818.778979
Median Absolute Deviation (MAD)	1278
Skewness	0.9922290787
Sum	32479755
Variance	2814614.782
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	4180	23.4%
2000	1077	6.0%
3000	640	3.6%
1500	465	2.6%
1000	429	2.4%
5000	364	2.0%
4000	273	1.5%
2500	213	1.2%
390	197	1.1%
1600	166	0.9%
Other values (3582)	9854	55.2%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	4180	23.4%
1	12	0.1%
2	13	0.1%
3	11	0.1%
4	6	< 0.1%
5	14	0.1%
6	6	< 0.1%
7	8	< 0.1%
8	6	< 0.1%
9	2	< 0.1%

Value	Count	Frequency (%)
8090	1	< 0.1%
8089	1	< 0.1%
8080	1	< 0.1%
8063	1	< 0.1%
8039	1	< 0.1%
8017	1	< 0.1%
8016	1	< 0.1%
8004	1	< 0.1%
8003	1	< 0.1%
8002	1	< 0.1%

pay_amt3
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	3351
Distinct (%)	18.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1508.541606

Minimum	0
Maximum	7200
Zeros	4575
Zeros (%)	25.6%
Negative	0
Negative (%)	0.0%
Memory size	139.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1180
Q3	2183.5
95-th percentile	4941
Maximum	7200
Range	7200
Interquartile range (IQR)	2183.5

Descriptive statistics

Standard deviation	1518.364686
Coefficient of variation (CV)	1.00651164
Kurtosis	0.9197424052
Mean	1508.541606
Median Absolute Deviation (MAD)	1120
Skewness	1.140298933
Sum	26939536
Variance	2305431.319
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	4575	25.6%
2000	1055	5.9%
1000	887	5.0%
3000	616	3.4%
1500	420	2.4%
5000	318	1.8%
4000	223	1.2%
2500	193	1.1%
1200	189	1.1%
390	175	1.0%
Other values (3341)	9207	51.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	4575	25.6%
1	8	< 0.1%
2	10	0.1%
3	7	< 0.1%
4	7	< 0.1%
5	8	< 0.1%
6	9	0.1%
7	9	0.1%
8	4	< 0.1%
9	5	< 0.1%

Value	Count	Frequency (%)
7200	3	< 0.1%
7178	1	< 0.1%
7171	1	< 0.1%
7169	1	< 0.1%
7164	1	< 0.1%
7158	1	< 0.1%
7142	1	< 0.1%
7122	1	< 0.1%
7100	5	< 0.1%
7069	1	< 0.1%

pay_amt4
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	3090
Distinct (%)	17.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1316.305353

Minimum	0
Maximum	6249
Zeros	4923
Zeros (%)	27.6%
Negative	0
Negative (%)	0.0%
Memory size	139.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1000
Q3	2000
95-th percentile	4206
Maximum	6249
Range	6249
Interquartile range (IQR)	2000

Descriptive statistics

Standard deviation	1400.574887
Coefficient of variation (CV)	1.064019745
Kurtosis	0.7451451057
Mean	1316.305353
Median Absolute Deviation (MAD)	1000
Skewness	1.164695852
Sum	23506581
Variance	1961610.014
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	4923	27.6%
1000	1152	6.5%
2000	968	5.4%
3000	634	3.6%
1500	382	2.1%
5000	322	1.8%
4000	243	1.4%
2500	210	1.2%
500	209	1.2%
390	179	1.0%
Other values (3080)	8636	48.4%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	4923	27.6%
1	11	0.1%
2	14	0.1%
3	8	< 0.1%
4	11	0.1%
5	5	< 0.1%
6	5	< 0.1%
7	6	< 0.1%
8	3	< 0.1%
9	2	< 0.1%

Value	Count	Frequency (%)
6249	1	< 0.1%
6218	1	< 0.1%
6206	1	< 0.1%
6200	2	< 0.1%
6196	1	< 0.1%
6185	1	< 0.1%
6174	1	< 0.1%
6170	1	< 0.1%
6137	1	< 0.1%
6131	1	< 0.1%

pay_amt5
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	2982
Distinct (%)	16.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1292.885821

Minimum	0
Maximum	5990
Zeros	5176
Zeros (%)	29.0%
Negative	0
Negative (%)	0.0%
Memory size	139.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	1000
Q3	2000
95-th percentile	4129.05
Maximum	5990
Range	5990
Interquartile range (IQR)	2000

Descriptive statistics

Standard deviation	1376.264676
Coefficient of variation (CV)	1.064490501
Kurtosis	0.547254358
Mean	1292.885821
Median Absolute Deviation (MAD)	1000
Skewness	1.113872725
Sum	23088355
Variance	1894104.459
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	5176	29.0%
1000	1116	6.2%
2000	1035	5.8%
3000	653	3.7%
1500	369	2.1%
5000	362	2.0%
4000	240	1.3%
500	216	1.2%
2500	190	1.1%
390	152	0.9%
Other values (2972)	8349	46.8%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	5176	29.0%
1	12	0.1%
2	6	< 0.1%
3	8	< 0.1%
4	3	< 0.1%
5	3	< 0.1%
6	4	< 0.1%
7	4	< 0.1%
8	3	< 0.1%
9	3	< 0.1%

Value	Count	Frequency (%)
5990	1	< 0.1%
5968	1	< 0.1%
5954	1	< 0.1%
5953	1	< 0.1%
5949	1	< 0.1%
5946	1	< 0.1%
5941	1	< 0.1%
5937	1	< 0.1%
5930	2	< 0.1%
5929	1	< 0.1%

pay_amt6
Real number (ℝ_≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct	2955
Distinct (%)	16.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1238.645145

Minimum	0
Maximum	5496
Zeros	5575
Zeros (%)	31.2%
Negative	0
Negative (%)	0.0%
Memory size	139.6 KiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	916.5
Q3	2000
95-th percentile	4000
Maximum	5496
Range	5496
Interquartile range (IQR)	2000

Descriptive statistics

Standard deviation	1349.44106
Coefficient of variation (CV)	1.089449279
Kurtosis	0.4464764644
Mean	1238.645145
Median Absolute Deviation (MAD)	916.5
Skewness	1.102567373
Sum	22119725
Variance	1820991.173
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	5575	31.2%
1000	1067	6.0%
2000	1021	5.7%
3000	660	3.7%
1500	388	2.2%
5000	335	1.9%
4000	235	1.3%
500	218	1.2%
2500	173	1.0%
390	144	0.8%
Other values (2945)	8042	45.0%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	5575	31.2%
1	15	0.1%
2	6	< 0.1%
3	5	< 0.1%
4	6	< 0.1%
5	4	< 0.1%
6	3	< 0.1%
7	2	< 0.1%
8	3	< 0.1%
9	4	< 0.1%

Value	Count	Frequency (%)
5496	1	< 0.1%
5495	1	< 0.1%
5485	1	< 0.1%
5483	1	< 0.1%
5454	1	< 0.1%
5430	2	< 0.1%
5419	1	< 0.1%
5411	1	< 0.1%
5410	1	< 0.1%
5407	1	< 0.1%

default.payment.next.month
Categorical

HIGH CORRELATION
HIGH CORRELATION

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	139.6 KiB

0	13154
1	4704

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	17858
Distinct characters	2
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	1
3rd row	0
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	13154	73.7%
1	4704	26.3%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0	13154	73.7%
1	4704	26.3%

Most occurring characters

Value	Count	Frequency (%)
0	13154	73.7%
1	4704	26.3%

Most occurring categories

Value	Count	Frequency (%)
Decimal Number	17858	100.0%

Most frequent character per category

Decimal Number

Value	Count	Frequency (%)
0	13154	73.7%
1	4704	26.3%

Most occurring scripts

Value	Count	Frequency (%)
Common	17858	100.0%

Most frequent character per script

Common

Value	Count	Frequency (%)
0	13154	73.7%
1	4704	26.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	17858	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
0	13154	73.7%
1	4704	26.3%

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Count
Matrix

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

First rows

	df_index	limit_bal	sex	education	marriage	age	pay_1	pay_2	pay_3	pay_4	pay_5	pay_6	prom_bill_amt	pay_amt1	pay_amt2	pay_amt3	pay_amt4	pay_amt5	pay_amt6	default.payment.next.month
0	0	20000.0	2	2	1	24	2	2	-1	-1	-2	-2	1284.000000	0.0	689.0	0.0	0.0	0.0	0.0	1
1	1	120000.0	2	2	2	26	-1	2	0	0	0	2	2846.166667	0.0	1000.0	1000.0	1000.0	0.0	2000.0	1
2	2	90000.0	2	2	2	34	0	0	0	0	0	0	16942.166667	1518.0	1500.0	1000.0	1000.0	1000.0	5000.0	0
3	3	50000.0	2	2	1	37	0	0	0	0	0	0	38555.666667	2000.0	2019.0	1200.0	1100.0	1069.0	1000.0	0
4	5	50000.0	1	1	2	37	0	0	0	0	0	0	39685.666667	2500.0	1815.0	657.0	1000.0	1000.0	800.0	0
5	7	100000.0	2	2	2	23	0	-1	-1	0	0	-1	2247.666667	380.0	601.0	0.0	581.0	1687.0	1542.0	0
6	8	140000.0	2	3	1	28	0	0	2	0	0	0	10868.666667	3329.0	0.0	432.0	1000.0	1000.0	1000.0	0
7	10	200000.0	2	3	2	34	0	0	2	0	0	-1	5744.500000	2306.0	12.0	50.0	300.0	3738.0	66.0	0
8	13	70000.0	1	2	2	30	1	2	2	0	0	2	56447.500000	3200.0	0.0	3000.0	3000.0	1500.0	0.0	1
9	14	250000.0	1	1	2	29	0	0	0	0	0	0	62265.166667	3000.0	3000.0	3000.0	3000.0	3000.0	3000.0	0

Last rows

	df_index	limit_bal	sex	education	marriage	age	pay_1	pay_2	pay_3	pay_4	pay_5	pay_6	prom_bill_amt	pay_amt1	pay_amt2	pay_amt3	pay_amt4	pay_amt5	pay_amt6	default.payment.next.month
17848	29981	50000.0	1	2	1	44	1	2	2	2	0	0	29009.833333	2300.0	1700.0	0.0	517.0	503.0	585.0	0
17849	29982	90000.0	1	2	1	36	0	0	0	0	0	0	10810.500000	1500.0	1500.0	1500.0	1200.0	2500.0	0.0	1
17850	29984	30000.0	1	2	2	38	-1	-1	-2	-1	-1	-1	1899.333333	923.0	2977.0	1999.0	3057.0	3319.0	1000.0	0
17851	29985	240000.0	1	1	2	30	-2	-2	-2	-2	-2	-2	0.000000	0.0	0.0	0.0	0.0	0.0	0.0	0
17852	29986	360000.0	1	1	2	35	-1	-1	-2	-2	-2	-2	370.000000	0.0	0.0	0.0	0.0	0.0	0.0	0
17853	29989	150000.0	1	1	2	35	-1	-1	-1	-1	-1	-2	2201.833333	9054.0	0.0	783.0	0.0	0.0	0.0	0
17854	29990	140000.0	1	2	1	41	0	0	0	0	0	0	108105.833333	6000.0	7000.0	4228.0	1505.0	2000.0	2000.0	0
17855	29991	210000.0	1	2	1	34	3	2	2	2	2	2	2500.000000	0.0	0.0	0.0	0.0	0.0	0.0	1
17856	29992	10000.0	1	3	1	43	0	0	0	-2	-2	-2	3200.333333	2000.0	0.0	0.0	0.0	0.0	0.0	0
17857	29999	50000.0	1	2	1	46	0	0	0	0	0	0	38479.000000	2078.0	1800.0	1430.0	1000.0	1000.0	1000.0	1

Overview

Variables

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Decimal Number

Most occurring scripts

Most frequent character per script

Common

Most occurring blocks

Most frequent character per block

ASCII

Interactions

Correlations

Pearson's r

Spearman's ρ

Kendall's τ

Phik (φk)

Cramér's V (φc)

Missing values

Sample

First rows

Last rows